The Egg Study published in the Journal of the American Medical Association this month has been highly publicised and criticised among evidence-based thinkers. As it has been adequately questioned as proof that eggs increase risk of cardiovascular disease, criticism has missed the elephant in the room: it was a negative study!
An elephant in the room is missed when our focus is shifted to a less important issue. In this case, the criticism has been mistakenly concentrated on the observational nature of the study. In this post, I will first explain why criticism is out of focus and second I will reveal the elephant in the room, explaining why it is a negative rather than a positive study.
Observational Study for Harm
In the first half of last century, 80% of western population were smokers and it was not considered harmful. Gastroenterologist Richard Doll investigated smoking as a possible cause for peptic ulcer and found no association. Then, he looked beyond his specialty and investigated lung cancer, in collaboration with famous statistician Austin Bradford Hill. This investigation led to the landmark article published in the British Medical Journal in 1950 demonstrating beyond a reasonable doubt that smoking leads to lung cancer. It was an observational study. And so far, of course, there is no randomised clinical trial to cigaret smoking versus placebo smoking to prove this causal relationship.
Would we criticise the ideia that smoking cause cancer because it came from an observational study? So why do we criticise the observational nature of the Egg Study for testing the ideia that eggs cause cardiovascular disease.
This criticism misses the difference between testing harm and testing beneficial effects, which relies on the burden of proof. In testing harm, a positive study will lead to the recommendation of “avoid” or “not to do”. In testing beneficial effect, a positive result will lead to the recommendation of “to do”. The negative consequence of an inappropriate recommendation of “to do” tends to be worse than a recommendation of “avoid”.
It is appropriate to criticise recommendations to eat or to take a medicine based on observational studies. Hormonal replacement therapy was recommended for cardiovascular prevention based on observational data and later randomised data indicated this therapy increases cardiovascular events. Also, so many dietary myths has been created by observational data.
On the other hand, in testing for harm, observational studies should not be considered inadequate as a rule of thumb. If two conditions are satisfied, well-designed observational studies might be taken as evidence for causation: first, a high biological plausibility, leading to high pre-test probability of the hypothesis; second, a very strong association: the hazard ratio for smoking and cancer or for alcohol and hepatic cirrhosis are both around 20, meaning a 1900% relative risk increase.
The hypothesis tested in the Egg Study was one of harm. So, instead of criticising the nature of the study, we must read it carefully in search for these two conditions.
Regarding pre-test probability of this hypothesis, it is difficult to comprehend how half an egg per day would be enough to increase risk of cardiovascular events, since eggs are just an small portion of dietary cholesterol, which is a weak determinant of plasma cholesterol. Second, the Egg Study shows a very weak association not fulfilling our condition for causation: hazard ratio = 1.06, just a 6% relative increase.
Therefore, this observational study should not be considered confirmatory in the sense that egg consumption is a risk factor for cardiovascular disease.
The Elephant in the Room
Along with egg consumption, the study evaluated total dietary cholesterol. The analysis of the direct effect of eggs and total dietary cholesterol, adjusted to each other, differentiates between the causal or non-causal nature of the relationship between eggs and cardiovascular events.
See how the analysis tells a history that makes sense:
Both eggs and total dietary cholesterol were associated with incident cardiovascular events during a median follow-up of 17.5 years. Each additional 300 mg of dietary cholesterol per day increased the hazard by 17% after adjustment for risk factors. Each additional half an egg per day would increase a tine 6% of hazard after adjustment for risk factors.
Now the multivariate analysis: when eggs were adjusted for total dietary cholesterol, eggs totally lost statistical significance. It suggests egg consumption is just a marker of a diet rich in cholesterol. To confirm this thought, when total dietary cholesterol were adjusted for eggs, its hazard ratio remained the same, equally significant. Thus, eggs are not a major determinant of total dietary cholesterol in this sample.
The first analysis makes the study negative for independent prediction value of eggs to cardiovascular events. The second analysis shows that the independent predictor is total dietary cholesterol, regardless of eggs.
The first analysis makes the study negative for independent prediction value of eggs to cardiovascular events. The second analysis shows that the independent predictor is total dietary cholesterol, regardless of eggs.
In addition with that, there is another trick in differentiating causation and confounding: to compare specific to non-specific mortality.
Mortality depends on a chain of events subjected to confounding. So the analysis of cause-specific mortality provides insight by comparing the different natures of deaths.
An effective way to differentiate causation and confounding is to test the association between the preditor and an “outside outcome”. Cardiovascular mortality is an “inside outcome” on the hypothesis that egg causes cardiovascular disease. Non-cardiovascular mortality has nothing to do with this hypothesis, being an “outside outcome”, which can be related with the same confounding as the “inside outcome” does. If the candidate risk factor is equally associated with the inside (cardiovascular mortality) and the outside outcome (non-cardiovascular mortality), the association has little to do with causation. The same confounding are mediating the two associations.
In this study, eggs consumption is associated with cardiovascular mortality. It may make sense. But it was similarly associated with non-cardiovascular mortality, which does not make sense. It indicates a strong influence of confounding in this epidemiological ecosystem.
These two interpretations make the Egg Study strongly negative for the hypothesis that eggs cause cardiovascular disease.
I admit it is harder to read an observational study in comparison with a randomised clinical trial. In observational studies, interpretation of results should take into consideration the multivariate analysis, which contains clues of the true reality.
My Diet
I eat one egg per day, at breakfast. The average consumption in US is half per day. If the association demonstrated in the study were causal, my egg habit would increase my risk by 6%. As a 49 year old male, with no risk factors, I have 5% risk of cardiovascular events. Eating my egg at breakfast would increase risk from 5% to 5,3%. Therefore, I’d keep my eggs even if it was a randomised clinical trial.
It makes me think. Normally, we first analyse if the evidence is true. Then, we ask if it is relevant. Maybe we should invert this order. We should ask first if the association makes a difference. If not, we should not care if it is true.
